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ISSN : 1226-9999(Print)
ISSN : 2287-7851(Online)
Korean J. Environ. Biol. Vol.41 No.2 pp.145-166
DOI : https://doi.org/10.11626/KJEB.2023.41.2.145

Molecular identification of selected parrot eggs using a non-destructive sampling method

Jung-Il Kim, Jong-Won Baek, Chang-Bae Kim*
Department of Biotechnology, Sangmyung University, Seoul 03016, Republic of Korea
* Corresponding author Chang-Bae Kim Tel. 02-2287-5288 E-mail. evodevo@smu.ac.kr

Contribution to Environmental Biology

▪ Using a non -destructive sampling method, 43 parrot eggs were identified as seven species.

▪ Results of this study might help control legal and illegal trade of parrot eggs.

16/03/2023 07/06/2023 16/06/2023

Abstract


Parrots have been threatened by global trade to meet their high demand as pets. Controlling parrot trade is essential because parrots play a vital role in the ecosystem. Accurate species identification is crucial for controlling parrot trade. Parrots have been traded as eggs due to their advantages of lower mortality rates and more accessible transport than live parrots. A molecular method is required to identify parrot eggs because it is difficult to perform identification using morphological features. In this study, DNAs were obtained from 43 unidentified parrot eggs using a non-destructive sampling method. Partial cytochrome b (CYTB ) gene was then successfully amplified using polymerase chain reaction (PCR) and sequenced. Sequences newly obtained in the present study were compared to those available in the GenBank by database searching. In addition, phylogenetic analysis was conducted to identify species using available sequences in GenBank along with sequences reported in previous studies. Finally, the 43 parrot eggs were successfully identified as seven species belonging to two families and seven genera. This non-destructive sampling method for obtaining DNA and molecular identification might help control the trade of parrot eggs and prevent their illegal trade.



초록


    1. INTRODUCTION

    Parrots (order Psittaciformes) play essential roles in the ecosystem by consuming the reproductive systems of plants and dispersing their seeds (Blanco et al. 2018). Despite their ecological significance, parrots are one of the most threatened species among birds because of the global trade to meet their high demand as pets (Pires 2012;Scheffers et al. 2019). Controlling the trade of parrots is crucial for their conservation (Scheffers et al. 2019). In this regard, the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) controls the parrot trade. CITES has controlled wildlife trade by listing species in appendices depending on the need for controlled trade (https:// cites.org). The Appendix I includes species threatened with extinction, and their trade is prohibited, while the Appendix II includes species that can be traded with export permits, and the trading of the listed species is closely monitored. A total of 413 parrot species belong- ing to three families and 89 genera have been reported (Del Hoyo 2020). Among these, 409 parrot species are listed in the CITES Appendices I and II (https://check list.cites.org). Despite the regulation of CITES, parrots have been illegally traded frequently in various countries (Sánchez-Mercado et al. 2021). Even if the trading of parrots is not regulated by CITES, these species might be captured often to sustain illegal trafficking (Olah et al. 2016;Formentão et al. 2021). In addition, most parrots are threatened due to habitat loss and fragmentation by human activity (Olah et al. 2016). The International Union for Conservation of Nature (IUCN) Red List of Threatened Species (https://www. iucnredlist.org) data confirm that the wild population of parrots is rapidly decreasing. Therefore, urgent actions must be taken to prevent the extinction of all parrots regardless of the CITES Appendices designation.

    Parrot eggs are widely traded due to the advantages of lower mortality rates and ease of transport than live parrots (Alacs and Georges 2008;Ortiz-von Halle 2018). These have been frequently traded illegally using purpose- built body vests to conceal the eggs (Coghlan et al. 2012). Hence, accurate species identification of these eggs is essential to control their legal and illegal trades (Coghlan et al. 2012). A molecular method is needed to identify parrot eggs because of the difficulty in identifying the species of parrot eggs based on eggshell morphology (Alacs and Georges 2008;Coghlan et al. 2012). Currently, the eggshell membrane has been used to extract DNA for identifying parrot eggs (Coghlan et al. 2012;Formentão et al. 2021). Previous studies have reported that high-quality DNA could be extracted from the eggshell membrane (Trimbos et al. 2009;Coghlan et al. 2012). Although this method successfully identified parrot eggs, it should destroy eggs. Typically, this destructive sampling method has been considered as a limitation to be overcome in wildlife forensics (Sahajpal and Goyal 2010;Ueland et al. 2020). This is because illegally traded eggs might be essential evidence in a court of law (Kumar et al. 2014). In addition, the use of destructive sampling method may be restricted or even forbidden for testing the eggs of endangered species (Richards et al. 2014). The methods that involve destroying the eggs to extract DNA should be carefully considered because those reduce the hatching success rate of the eggs (Khabisi et al. 2012). Therefore, a nondestructive sampling method that maintains the intactness of eggs might be helpful in identifying the eggs of both endangered and non-endangered parrots. Egloff et al. (2009) suggested a non-destructive method of obtaining eggshell powder by grinding the surface of eggs. This method could be used to obtain maternal DNA from the eggshell because epithelial cells are abraded from the surface of the oviduct wall and incorporated into the matrix of the eggshell (Egloff et al. 2009). This method may be more appropriate for controlling the trade of parrot eggs (Oskam et al. 2010).

    The DNA barcoding technique has been globally used for species identification of wildlife (Khedkar et al. 2016;Dalton et al. 2020;Park et al. 2022). This technique can also be applied to assign an unknown sample that is difficult to identify morphologically to a known species (Meyer and Paulay 2005). Mitochondrial genes have been widely used as a major target in animal DNA barcoding (Hebert et al. 2003). Among the mitochondrial genes, cytochrome c oxidase subunit I (COI) and cytochrome b (CYTB) genes have been universally applied for the identification of avian species (Hebert et al. 2004;Kim et al. 2020). In particular, the CYTB has been a representative gene in identifying avian species (Branicki et al. 2003). There are also more available CYTB gene sequences of parrots than other mitochondrial genes in molecular databases, such as the GenBank (Coghlan et al. 2012).

    Despite the importance of the identification of parrot eggs without their destruction, there have been no study to identify parrot eggs by using a non-destructive sampling method to obtain their DNA. In the present study, the DNA of 43 unidentified parrot eggs was obtained without destroying the eggs. The partial CYTB gene was amplified from the DNA and then sequenced. By using database searching and phylogenetic analysis, the eggs have been clearly identified into seven species.

    2. MATERIALS AND METHODS

    A total of 43 unfertilized parrot eggs were obtained from two pet shops located in Incheon and Seoul, South Korea. These were obtained without knowing the species that laid the eggs. Those were used without predicting species by their morphological features due to the extreme difficulty of morphological identification of the eggs. These were numbered from PE 01 to PE 43 and stored at -80°C to prevent rot. A non-destructive sampling method suggested by Egloff et al. (2009) was modified and used in the present study. First, the surface of parrot eggs was cleaned using 70% ethanol and DNA AWAY (Molecular BioProducts, USA) to remove any foreign DNA on the parrot egg surface. Then, all other residues were removed using distilled water. Finally, the surface of parrot eggs was dried using sterile gauze by removing all the remaining liquids. To obtain eggshell powder, the parrot egg was placed on a weighing paper that was placed on a plastic 50-mL conical tube rack. The egg was ground using a mini grinder equipped with a round-shaped diamond grinding burr for minimal powder loss. The grinding burr was cleaned by the same method used for cleaning the parrot eggs to prevent cross-contamination among parrot eggs examined in this study. In addition, the weighing paper was replaced with a new one before collecting a new eggshell powder. 10 mg of eggshell powder was collected in a 1.5 mL Eppendorf tube. All eggshell powder samples were stored at -80°C for further experiments.

    Total DNA was extracted from the eggshell powder samples using a QIAamp DNA Micro Kit (Qiagen, Valencia, CA, USA), according to the manufacturer’s instructions. The purity and concentration of extracted DNA were measured using the MaestroNano spectrophotometer (Maestrogen, Hsinchu, Taiwan). The purity of DNA was measured using a 260 nm/280 nm ratio (A260/A280) and 260 nm/230 nm ratio (A260/A230), which indicate the estimated levels of protein contamination and organic contamination, respectively. The partial CYTB gene was amplified using the primer pairs Mte (5′ GCA AAT AGG AAG TAT CAT TCT GG 3′) (Fritz et al. 2006) and MT-A1 (5′ CAA CAT CTC AGC ATG ATG AAA CTT CG 3′) (Wink and Sauer-Gürth 2000). PCR was performed using a 20-μL sample comprising 1.0 U of Taq polymerase with 10 μL of 2×Dye- Mix (Enzynomics, Korea), 1 μL of each primer (10 pmol μL-1), 3 to 5 μL of DNA, and distilled water up to 20 μL. The reaction conditions were as follows: initial denaturation for 2 min at 95°C, 35 cycles of 1 min at 95°C, 45 s at 48°C, 1 min at 72°C, and a final elongation step for 5 min at 72°C. The PCR products were evaluated using 1% (w/v) agarose gels in 1% tris-acetate buffer. The PCR products were directly sequenced with the primer pairs using the Sanger sequencing method.

    The consensus sequence was extracted from forward and reverse direction sequences by alignment using Geneious 9.1 software (Kearse et al. 2012). These final sequences were deposited in GenBank under accession numbers OQ413731-OQ413773. The sequences were compared with those from the GenBank through the BLAST search, and the top one sequence showing the highest sequence similarity selected (Altschul et al. 1997). The additional CYTB gene sequences of congeneric species were retrieved from the GenBank to analyze the phylogeny of species examined in this study. The sequences of closely related species of each species were selected as an outgroup of the phylogeny based on the phylogenies of the parrots analyzed in previous studies (Ribas and Miyaki 2004;Ribas et al. 2006;Manegold and Podsiadlowski 2014;Kim et al. 2021;Kim et al. 2022). The sequences were aligned using MAFFT (Katoh and Standley 2013) in Geneious 9.1 software with the default setting. A suitable region for phylogenetic analysis was selected using GBlocks (Talavera and Castresana 2007) in the Phylogeny.fr pipeline with the default setting (Dereeper et al. 2008). The best-fit substitution model was determined using jMoedlTest (Darriba et al. 2012). Length and best-fit substitution model for each CYTB gene sequence dataset to construct phylogenies of the species examined in this study are presented in Table S1. Phylogenetic analysis was conducted by Maximum Likelihood (ML) using IQTREE v1.6.12 (Nguyen et al. 2015). Node supports were calculated using 5,000 bootstrap replicates. ML method has been commonly used to construct phylogeny because this typically presents the compromise between accuracy and computational requirements (Kang et al. 2022;Maio et al. 2023). The resulting trees were visualized and edited using FigTree v1.4.3 (http://tree.bio.ed. ac.uk/software/figtree/). Genetic distances were evaluated using Kimura-2-parameter (K2P) distance model (Kimura 1980) in MEGA X software (Kumar et al. 2018) using the same dataset of analyzing to construct each phylogeny.

    3. RESULTS AND DISCUSSION

    The values of A260/A280 and A230/A260 of the egg samples in this study varied from 1.092 to 2.703 and from 0.515 to 2.903, respectively (data not shown). The values of A260/A280 and A260/A230 for pure DNA are 1.8 and 2.0, respectively (Qamar et al. 2017;Sloan et al. 2021). The purity of the extracted DNA was lower than that of the pure DNA. The concentration of DNA varied from 5.09 to 101.61 ng μL-1 (data not shown). The eggshell consists of calcium carbonate and an organic matrix such as a cuticle layer (Oskam et al. 2010). Typically, calcium ions and cuticles have been known as inhibitors of DNA extraction (Mohammadi et al. 2017;Sloan et al. 2021). The low purity and concentration of DNA extracted from 43 parrot eggs might be due to these components of eggs. The DNA samples extracted from parrot eggs were successfully amplified by PCR for the marker on the mitochondrial CYTB gene despite the low purity and concentration of DNA. Among the examined samples, seven representative PCR products identified as different species; Nymphicus hollandicus (Kerr 1792), Pyrrhura molinae (Massena and Souancé 1854), Agapornis roseicollis (Vieillot 1818), Aratinga solstitialis (Linnaeus 1758), Myiopsitta monachus (Boddaert 1783), Eclectus roratus (Müller 1776), and Melopsittacus undulatus (Shaw 1805), are presented in Fig. 1. The partial CYTB gene sequences were obtained from the PCR products of all parrot egg samples.

    The sequence having the highest sequence similarity with the 43 sequences that were newly sequenced in the study are presented in Table 1. The CYTB gene sequences of the samples demonstrated >99.71% sequence similarity with the available sequences of seven species in the database (Table 1). Among those, 14 sequences (accession number: OQ413753-OQ413766) showed the highest similarity with the sequences of Eclectus roratus. Further, 13 sequences (accession number: OQ 413731-OQ413743) presented the highest similarity with sequences of Nymphicus hollandicus. In addition, eight (accession number: OQ413744-OQ413751), four (accession number: OQ413769-OQ413772), two (accession number: OQ413767 and OQ413768) sequences showed the highest similarity with sequences of Agapornis roseicollis, Myiopsitta monachus, and Melopsittacus undulatus, respectively. The sequences designated as accession numbers: OQ413752 and OQ413773 showed the highest similarity with the sequences of Aratinga solstitialis and Pyrrhura molinae, respectively.

    For species identification, the phylogenies of these seven species were analyzed using the new sequences obtained in this study and the CYTB gene sequences were retrieved from the database. The phylogenies of Agapornis roseicollis, Aratinga solstitialis, and P. molinae were analyzed using the available sequences of each congeneric species. The best-fit substitution model of each dataset used to analyze the phylogenies of these species is presented in Table S1. The phylogeny of Agapornis roseicollis is presented in Fig. 2. The sequence Psittaculirostris desmarestii (Desmarest 1826) and Psittaculirostris edwardsii (Oustalet 1885) closely related to Agapornis, were used as an outgroup (Manegold and Podsiadlowski 2014). Eight sequences (accession number: OQ413744-OQ413751) that were newly sequenced in the present study were clustered along with the sequences of Agapornis roseicollis, and this branch was supported with high bootstrap values (Fig. 2). Agapornis roseicollis is a sister taxon of the Agapornis personatus group comprising Agapornis fischeri (Reichenow 1887), Agapornis lilianae (Shelley 1894), and Agapornis personatus (Reichenow 1887) in the phylogeny analyzed in this study. The relationship among species in the Agapornis was congruent with the finding of a previous study (Manegold and Podsiadlowski 2014). The phylogenetic relationship of Aratinga is presented in Fig. 3. For constructing this relationship, the outgroup consisted of the sequence of Primolius couloni (Sclater 1876) and Primolius maracana (Vieillot 1816), closely related to Aratinga (Ribas and Miyaki 2004). A sequence that was newly obtained in this study (accession number: OQ413752) was included in the branch of Aratinga solstitialis (Fig. 3). However, the bootstrap support value of this branch was relatively low, probably due to the close relationship between Aratinga solstitialis, Aratinga auricapillus (Kuhl 1820), and Aratinga jandaya (Gmelin 1788) (Ribas and Miyaki 2004). This close relationship among these species might be caused by the recent divergence of these three species during the Pleistocene (Ribas and Miyaki 2004).

    The genus Pyrrhura is phylogenetically divided into three major clades, and P. molinae was included in the clade along with P. frontalis (Vieillot 1818), P. lepida (Wagler 1832), and P. perlata (Spix 1824) (Ribas et al. 2006). The sequences of the ten Pyrrhura species belonging to the clade, including P. molinae were retrieved to analyze the phylogenetic relationships of this clade. The sequences of Anodorhynchus hyacinthinus (Latham 1790) and Anodorhynchus leari (Bonaparte 1856) were used as an outgroup (Ribas et al. 2006). The new sequence reported in this study (accession number: OQ 413773) was clustered with the sequences of P. molinae, and it was supported with high bootstrap values (Fig. 4). The sister taxon of P. molinae was P. frontalis in the phylogeny constructed in this study. However, P. molinae was a sister taxon of the branch that included P. lepida and P. perlata in the phylogeny based on the mitochondrial CYTB gene and control region in a previous study (Ribas et al. 2006). The difference in the phylogenetic relationships among these species may be attributed to the use of only CYTB gene in constructing the phylogeny in the present study. In future studies, more mitochondrial genes should be used to analyze the phylogenetic relationship among P. frontalis, P. lepida, P. molinae, and P. perlata.

    The four monotypic species whose phylogenies were examined in this study are listed as follows: E. roratus, Myoipsitta monachus, Melopsittacus undulatus, and N. hollandicus. The phylogenies were constructed using the available CYTB gene sequences of the most closely related genera of each species. The most closely related genera of the four species were selected based on the phylogenies of the parrots analyzed using complete mitochondrial genomes reported in previous studies (Kim et al. 2021, 2022). The available sequences of the genera Psittacula, Brotogeris, and Probosciger were used to construct phylogenies of E. roratus, Myiopsitta monachus, and N. hollandicus, respectively. Since Lorius and Trichoglossus genera have been reported as sister taxa of Melopsittacus undulatus, the available sequences of both genera were used to construct the phylogenetic tree of this species (Kim et al. 2022). The species list and accession numbers of the sequences of the most closely related genera of each of four monotypic species retrieved from the database are presented in Table S2. The best-fit substitution model of each dataset used to construct the phylogenies of these four species is presented in Table S1. 14 sequences (accession number: OQ413 753-OQ413766) were clustered with the sequences of E. roratus, that showed high bootstrap support values (Fig. S1). 13 sequences (accession number: OQ413 731-OQ413743) were included in the branch of N. hollandicus, supported with high bootstrap values (Fig. S2). In addition, four sequences (accession number: OQ 413769-OQ413772) were clustered with the sequences of Myiopsitta monachus, and it showed high bootstrap support values (Fig. S3). Two sequences (accession number: OQ413767 and OQ413768) were included in the branch of Melopsittacus undulatus, and were supported with high bootstrap values (Fig. S4).

    The genetics distance of seven species examined in this study was calculated using the same dataset analyzed to construct the phylogeny (Table S3). The maximum intra-specific distance varied from 0.003 for Myiopsitta monachus to 0.027 for E. roratus. The lowest minimum inter-specific distance was 0.010 for Aratinga solstitialis, and the highest was 0.135 for N. hollandicus. In all seven species examined in the present study, the minimum inter-specific distance was higher than the maximum intra-specific distance.

    Representative images of seven species are presented in Fig. 5. The native distribution of those is presented in Table S4. Three species, N. hollandicus, E. roratus, and Melopsittacus undulatus, are native to Australia and Southeast Asia countries. The other three, Aratinga solstitialis, Myiopsitta monachus, and P. molinae, are natively distributed in South America countries, and another species, Agapornis roseicollis, are native to Angola, Namibia, and South Africa. Aratinga solstitialis is categorized as Endangered, and others are Least Concern on the IUCN Red List of Threatened Species (Table S4). In addition, four of seven species are listed in CITES Appendix II for controlling their trade (Table S4). According to the report from the National Institution of Biological Resources (NIBR) in 2016, 50 parrots were imported into Korea from 2009 to 2014 (NIBR 2016). Among seven species examined in this study, four species, Aratinga solstitialis, E. roratus, Myiopsitta monachus, and P. molinae, were listed in the list of imported parrots (NIBR 2016).

    In conclusion, DNA was successfully obtained from 43 unidentified parrot eggs by using a non-destructive sampling method, and then PCR and DNA sequencing were executed from the extracted DNA. As a result, these eggs were identified as seven parrot species belonging to two families and seven genera by sequence comparison with sequences of the GenBank using database search and phylogenetic analysis using available sequences retrieved from the GenBank. The non-destructive sampling method to obtain DNA from parrot eggs and molecular identification might help to control the trade of parrot eggs and prevent illegal trade of those. However, only 43 samples from seven parrot species were analyzed in this study. To ensure the usefulness of molecular identification and the non-destructive sampling method to identify parrot eggs, more comprehensively sampled parrot eggs, particularly heavily traded legally or illegally, should be investigated in future studies.

    ACKNOWLEDGEMENTS

    The authors thank Bird Palace in Incheon and Bird Forest in Seoul for supplying samples.

    CRediT authorship contribution statement

    JI Kim: Conceptualization, Methodology, Investigation, Writing-Original Draft. JW Baek: Methodology, Investigation, Data Curation. CB Kim: Conceptualization, Methodology, Writing-Original Draft, Writing-Review & Editing.

    Declaration of Competing Interest

    The authors declare no conflicts of interest.

    Figure

    KJEB-41-2-145_F1.gif

    Seven representative PCR products for partial mitochondrial cytochrome b (CYTB ) gene of egg samples identified as different species. L, 1 kb ladder; 1. PE 01 identified as Nymphicus hollandicus; 2, PE 05 as Pyrrhura molinae; 3, PE 10 as Agapornis roseicollis; 4, PE 14 as Myiopsitta monachus; 5, PE 18 as Eclectus roratus; 6, PE 27 as Melopsittacus undulatus; 7, PE 29 as Aratinga solstitialis; 8, Negative control. Sample numbers are presented in Table 1.

    KJEB-41-2-145_F2.gif

    Phylogeny of genus Agapornis based on partial mitochondrial cytochrome b (CYTB ) gene. Black circles indicate eight individuals investigated in this study. Their sample numbers are presented in parentheses. Accession numbers of CYTB sequences retrieved from GenBank are presented with species. Maximum Likelihood (ML) bootstrap values≥50 are shown at nodes. Scale bar indicates nucleotide substitutions per site.

    KJEB-41-2-145_F3.gif

    Phylogeny of genus Aratinga based on partial mitochondrial cytochrome b (CYTB ) gene. Black circle indicates the one individual examined in this study. The sample number of that is presented in parentheses. Accession numbers of the CYTB sequences retrieved from GenBank are presented with the species. Maximum Likelihood (ML) bootstrap values≥50 are shown at nodes. Scale bar indicates nucleotide substitutions per site.

    KJEB-41-2-145_FS1.gif

    Phylogeny of Eclectus roratus based on partial mitochondrial cytochrome b (CYTB ) gene. Black circles indicate fourteen sequences investigated in this study. Sample numbers are presented in parentheses. Sequences of Prioniturus luconensis and Prioniturus mada, a closely related genus to Eclectus and Psittacula, were used as outgroup. Accession numbers of CYTB sequences retrieved from GenBank are presented with the species. Branch of genus Psittacula is presented as collapsing. Accession numbers of CYTB sequences of the genus Psittacula retrieved from GenBank are presented in Table S1. Maximum Likelihood (ML) bootstrap values≥50 are shown at nodes. Scale bar indicates nucleotide substitutions per site.

    KJEB-41-2-145_FS2.gif

    Phylogeny of Melopsittacus undulatus based on partial mitochondrial cytochrome b (CYTB ) gene. Black circles indicate two sequences investigated in this study. Sample numbers of those are presented in parentheses. Sequences of Agapornis nigrigenis and Agapornis personatus, a closely related genus to those three genera, were used as outgroup. Accession numbers of CYTB sequences retrieved from GenBank are presented with the species. Branch of genera Lorius and Trichoglossus is presented as collapsing. Accession numbers of CYTB sequences of genera Lorius and Trichoglossus retrieved from GenBank are presented in Table S1. Maximum Likelihood (ML) bootstrap values≥50 are shown at nodes. Scale bar indicates nucleotide substitutions per site.

    KJEB-41-2-145_FS3.gif

    Phylogeny of Myiopsitta monachus based on partial mitochondrial cytochrome b (CYTB ) gene. Black circles indicate four sequences investigated in this study. Sample numbers of those are presented in parentheses. Sequences of Forpus passerinus and Forpus xanthopterygius, a closely related genus to Myiopsitta and Brotogeris, were used as outgroup. Accession numbers of CYTB sequences retrieved from GenBank are presented with the species. Branch of genus Brotogeris is presented as collapsing. Accession numbers of CYTB sequences of the genus Brotogeris retrieved from GenBank are presented in Table S1. Maximum Likelihood (ML) bootstrap values≥50 are shown at the nodes. Scale bar indicates nucleotide substitutions per site.

    KJEB-41-2-145_FS4.gif

    Phylogeny of Nymphicus hollandicus based on partial mitochondrial cytochrome b (CYTB ) gene. Black circles indicate thirteen sequences investigated in this study. Sample numbers of those are presented in parentheses. Sequences of Zanda baudinii and Zanda latirostris, a closely related genus to Nymphicus and Probosciger, were used as outgroup. Accession numbers of CYTB sequences retrieved from GenBank are presented with the species. Branch of genus Probosciger is presented as collapsing. Accession numbers of CYTB sequences of genus Probosciger retrieved from GenBank are presented in Table S1. Maximum Likelihood (ML) bootstrap values≥50 are shown at nodes. Scale bar indicates nucleotide substitutions per site.

    KJEB-41-2-145_F4.gif

    Phylogeny of one major clade of genus Pyrrhura, including Pyrrhura molinae, based on partial mitochondrial cytochrome b (CYTB ) gene. Black circle indicates the one individual examined in this study. Sample number is presented in parentheses. Accession numbers of CYTB sequences retrieved from GenBank are presented with the species. Maximum Likelihood (ML) bootstrap values≥50 are shown at nodes. Scale bar indicates nucleotide substitutions per site.

    KJEB-41-2-145_F5.gif

    Representative images of seven species examined in this study. A, Nymphicus hollandicus; B, Agapornis roseicollis; C, Aratinga solstitialis; D, Eclectus roratus (male); E, Eclectus roratus (female); F, Melopsittacus undulatus; G, Myiopsitta monachus; H, Pyrrhura molinae. Photo credit: A, Zefry; B, Tim; C, H. Zell; D, Sheba; E, Dany Sloan; F, Benjamint444; G, Bernard DUPONT; H, Brandon Lim.

    Table

    Length and best-fit substitution model for each mitochondrial cytochrome b (CYTB ) gene sequence dataset to construct phylo - genies of seven species examined in this study

    BLAST searching results comparing partial mitochondrial cytochrome b (CYTB ) gene sequences obtained from 43 parrot eggs to sequences of GenBank database

    Species list and accession numbers of mitochondrial cytochrome b (CYTB ) gene sequences of five genera retrieved from Gen- Bank to construct phylogenies of Eclectus roratus, Melopsittacus undulats, Myiopsitta monachus, and Nymphicus hollandicus in this study

    Intra -specific and inter-specific distances (%) analyzed using partial CYTB gene sequences of 43 parrot eggs newly sequenced in the present study and those of congeneric species retrieved from GenBank

    Detailed information of examined species

    Reference

    1. Alacs E and A Georges.2008. Wildlife across our borders: A review of the illegal trade in Australia. Aust. J. Forensic Sci. 40:147-160.
    2. Altschul SF , TL Madden, AA Schäffer, J Zhang, Z Zhang, W Miller and DJ Lipman.1997. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389-3402.
    3. Blanco G , F Hiraldo and JL Tella.2018. Ecological functions of parrots: An integrative perspective from plant life cycle to ecosystem functioning. Emu 118:36-49.
    4. Branicki W , T Kupiec and R Pawlowski.2003. Validation of cytochrome b sequence analysis as a method of species identification. J. Forensic Sci. 48:1-5.
    5. Coghlan ML , NE White, L Parkinson, J Haile, PBS Spencer and M Bunce.2012. Egg forensics: An appraisal of DNA sequencing to assist in species identification of illegally smuggled eggs. Forensic Sci. Int.-Genet. 6:268-273.
    6. Dalton DL , M de Bruyn, T Thompson and A Kotzé.2020. Assessing the utility of DNA barcoding in wildlife forensic cases involving South African antelope. Forensic Sci. Int. -Rep. 2:100071.
    7. Darriba D , GL Taboada, R Doallo and D Posada.2012. jModelTest 2: more models, new heuristics and parallel computing. Nat. Methods 9:772-772.
    8. Del Hoyo J. 2020. All the Birds of the World. Lynx Edicions. Barcelona, Spain.
    9. Dereeper A , V Guignon, G Blanc, S Audic, S Buffet, F Chevenet, JF Dufayard, S Guindon, V Lefort, M Lescot, JM Claverie and O Gascuel.2008. Phylogeny.fr: robust phylogenetic analysis for the non-specialist. Nucleic Acids Res. 36:W465-W469.
    10. Egloff C , A Labrosse, C Hebert and D Crump.2009. A non-destructive method for obtaining maternal DNA from avian eggshells and its application to embryonic viability determination in herring gulls (Larus argentatus). Mol. Ecol. Resour. 9:19-27.
    11. Formentão L , AS Saraiva and AR Marrero.2021. DNA barcoding exposes the need to control the illegal trade of eggs of nonthreatened parrots in Brazil. Conserv. Genet. Resour. 13:275- 281.
    12. Fritz U , M Auer, A Bertolero, M Cheylan, T Fattizzo, AK Hundsdörfer, MM Sampayo, JL Pretus, P ŠIrok Ý and M Wink.2006. A rangewide phylogeography of hermann's tortoise, Testudo hermanni (Reptilia: Testudines: Testudinidae): Implications for taxonomy. Zool. Scr. 35:531-543.
    13. Hebert PDN , A Cywinska, SL Ball and HR DeWaard.2003. Biological identifications through DNA barcodes. Proc. R. Soc. BBiol. Sci. 270:313-321.
    14. Hebert PDN , MY Stoeckle, TS Zemlak and CM Francis.2004. Identification of birds through DNA barcodes. PLoS Biol. 2:e312.
    15. Kang S , T Kim, J Lee, J Ki and JH Kim.2022. First report of Amphidinium fijiense (Dinophyceae) from the intertidal zone of a sandy beach of Jeju Island, Korea. Korean J. Environ. Biol. 40:497-509.
    16. Katoh K and DM Standley.2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30:772-780.
    17. Kearse M , R Moir, A Wilson, S Stones-Havas, M Cheung, S Sturrock, S Buxton, A Cooper, S Markowitz, C Duran, T Thierer, B Ashton, P Meintjes, A Drummond and A Notes.2012. Geneious basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 282:1647-1649.
    18. Khabisi MM , A Salahi and SN Mousavi.2012. The influence of egg shell crack types on hatchability and chick quality. Turk. J. Vet. Anim. Sci. 36:289-295.
    19. Khedkar GD , SB Abhayankar, D Nalage, SN Ahmed and CD Khedkar.2016. DNA barcode based wildlife forensics for resolving the origin of claw samples using a novel primer cocktail. Mitochondrial DNA Part A 27:3932-3935.
    20. Kim JI , TD Do, D Lee, Y Yeo and CB Kim.2020. Application of cytochrome b gene sequences for identification of parrots from Korean zoos. Anim. Syst. Evol. Divers. 36:216-221.
    21. Kim JI , TD Do, Y Choi, Y Yeo and CB Kim.2021. Characterization and comparative analysis of complete mitogenomes of three Cacatua parrots (Psittaciformes: Cacatuidae). Genes 12:209.
    22. Kim JI , TD Do, Y Yeo and CB Kim.2022. Comparative analysis of complete mitochondrial genomes of three Trichoglossus species (Psittaciformes: Psittacidae). Mol. Biol. Rep. 49:9121- 9127.
    23. Kimura M. 1980. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16:111-120.
    24. Kumar S , G Stecher, M Li, C Knyaz and K Tamura.2018. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35:1547-1549.
    25. Kumar VP , D Kumar and SP Goyal.2014. Wildlife DNA forensic in curbing illegal wildlife trade: species identification from seizures. Int. J. Forensic Sci. Pathol. 2:38-42.
    26. Maio D , P Kalaghatgi, Y Turakhia, R Corbett-Detig, BQ Minh and N Goldman.2023. Maximum likelihood pandemic-scale phylogenetics. Nat. Gen. 55:746-752.
    27. Manegold A and L Podsiadlowski.2014. On the systematic position of the Black-collared Lovebird Agapornis swindernianus (Agapornithinae, Psittaciformes). J. Ornithol. 155:581-589.
    28. Meyer CP and G Paulay.2005. DNA barcoding: Error rates based on comprehensive sampling. PLoS Biol. 3:e422.
    29. Mohammadi A , AG Alvanegh, M Khafaei, SH Azarian, M Naderi, E Kiyani, A Miri, H Bahmani, M Ramezani and M Tavallaci.2017. A new and efficient method for DNA extraction from human skeletal remains usable in DNA typing. J. Appl. Biotechnol. Rep. 4:609-614.
    30. Nguyen LT , HA SchmidtH, A Von Haeseler and BQ Minh.2015. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32:268-274.
    31. NIBR.2016. The Guideline for Import and Export Review of CITES Species. National Institute of Biological Resources. Incheon, Korea.
    32. Olah G , SH Butchart, A Symes, IM Guzmán, R Cunningham, DJ Brightsmith and R Heinsohn.2016. Ecological and socio-economic factors affecting extinction risk in parrots. Biodivers. Conserv. 25:205-223.
    33. Ortiz-von Halle B. 2018. Bird’s-Eye View: Lessons from 50 Years of Bird Trade Regulation & Conservation in Amazon Countries. TRAFFIC. Cambridge, U.K.
    34. Oskam CL , J Haile, E McLay, P Rigby, ME Allentoft, ME Olsen, C Bengtsson, GH Miller, J Schwenniger, C Jacomg, R Walter, A Baynes, J Dortch, M Parker-Pearson, MTP Gilbert, RN Holdaway, E Willerslev and M Bunce.2010. Fossil avian eggshell preserves ancient DNA. Proc. R. Soc. B-Biol. Sci. 277:1991- 2000.
    35. Qamar W , MR Khan and A Arafah.2017. Optimization of conditions to extract high quality DNA for PCR analysis from whole blood using SDS-proteinase K method. Saudi J. Biol. Sci. 24:1465-1469.
    36. Park HJ , SY Byeon, SR Park and HJ Lee.2022. Temporal variation in the community structure of green tide forming macroalgae (Chlorophyta; genus Ulva) on the coast of Jeju Island, Korea based on DNA barcoding. Korean J. Environ. Biol. 40:464-476.
    37. Pires SF. 2012. The illegal parrot trade: A literature review. Glob. Crime 13:176-190.
    38. Ribas CC and CY Miyaki.2004. Molecular systematics in Aratinga parakeets: Species limits and historical biogeography in the ‘solstitialis’ group, and the systematic position of Nandayus nenday. Mol. Phylogenet. Evol. 30:663-675.
    39. Ribas CC , L Joseph and CY Miyaki.2006. Molecular systematics and patterns of diversification in Pyrrhura (Psittacidae), with special reference to the picta-leucotis complex. Auk 123: 660-680.
    40. Richards NL , S Hall, NM Harrison, L Gautam, KS Scott, G Dowling, Z Irene and I Fajardo.2014. Merging wildlife and environmental monitoring approaches with forensic principles: application of unconventional and non-invasive sampling in eco-pharmacovigilance. J. Forensic Res. 5:228.
    41. Sahajpal V and SP Goyal.2010. Identification of a forensic case using microscopy and forensically informative nucleotide sequencing (FINS): A case study of small Indian civet (Viverricula indica). Sci. Justice 50:94-97.
    42. Sánchez-Mercado A , JR Ferrer-Paris, JP Rodríguez and JL Tella.2021. A literature synthesis of actions to tackle illegal parrot trade. Diversity 13:191.
    43. Scheffers BR , BF Oliveira, I Lamb and DP Edwards.2019. Global wildlife trade across the tree of life. Science 366:71-76.
    44. Sloan S , CJ Jenvey, D Piedrafita, S Preston and MJ Stear.2021. Comparative evaluation of different molecular methods for DNA extraction from individual Teladorsagia circumcincta nematodes. BMC Biotechnol. 21:35.
    45. Talavera G and J Castresana.2007. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst. Biol. 56:564-577.
    46. Trimbos KB , J Broekman, R Kentie, CJ Musters and GR de Snoo.2009. Using eggshell membranes as a DNA source for population genetic research. J. Ornithol. 150:915-920.
    47. Ueland M , A Brown, C Bartos, GJ Frankham, RN Johnson and SL Forbes.2020. Profiling volatilomes: a novel forensic method for identification of confiscated illegal wildlife items. Separations 7:5.
    48. Wink M and H Sauer-Gürth.2000. Advances in the molecular systematics of African raptors. pp. 135-147. In: Raptors at Risk (Chancellor RD and BU Meyburg, eds.). WWGBP/Handcock House. Surrey, B.C.

    Vol. 40 No. 4 (2022.12)

    Journal Abbreviation 'Korean J. Environ. Biol.'
    Frequency quarterly
    Doi Prefix 10.11626/KJEB.
    Year of Launching 1983
    Publisher Korean Society of Environmental Biology
    Indexed/Tracked/Covered By

    Contact info

    Any inquiries concerning Journal (all manuscripts, reviews, and notes) should be addressed to the managing editor of the Korean Society of Environmental Biology. Yongeun Kim,
    Korea University, Seoul 02841, Korea.
    E-mail: kyezzz@korea.ac.kr /
    Tel: +82-2-3290-3496 / +82-10-9516-1611