Abstract
Background
In nucleotide public repositories, studies discovered data errors which resulted in incorrect species identification of several accipitrid raptors considered for conservation. Mislabeling, particularly in cases of cryptic species complexes and closely related species, which were identified based on morphological characteristics, was discovered. Prioritizing accurate species labeling, morphological taxonomy, and voucher documentation is crucial to rectify spurious data.
Objective
Our study aimed to identify an effective DNA barcoding tool that accurately reflects the efficiency status of barcodes in raptor species (Accipitridae).
Methods
Barcode sequences, including 889 sequences from the mitochondrial cytochrome c oxidase I (COI) gene and 1052 sequences from cytochrome b (Cytb), from 150 raptor species within the Accipitridae family were analyzed.
Results
The highest percentage of intraspecific nearest neighbors from the nearest neighbor test was 88.05% for COI and 95.00% for Cytb, suggesting that the Cytb gene is a more suitable marker for accurately identifying raptor species and can serve as a standard region for DNA barcoding. In both datasets, a positive barcoding gap representing the difference between inter-and intra-specific sequence divergences was observed. For COI and Cytb, the cut-off score sequence divergences for species identification were 4.00% and 3.00%, respectively.
Conclusion
Greater accuracy was demonstrated for the Cytb gene, making it the preferred primary DNA barcoding marker for raptors.
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Data availability
The full dataset and metadata used in this study are available from the Dryad Digital Repository. Data set: https://datadryad.org/stash/share/XofELd3yZewjORV3D5DvZrRVK92ZkaGasj10bl7Pw9I
References
Aliabadian M, Kaboli M, Nijman V, Vences M (2008) Molecular identification of birds: performance of distance-based DNA barcoding in three genes to delimit parapatric species. PLoS ONE 4:e4119. https://doi.org/10.1371/journal.pone.0004119
Aliabadian M, Beentjes KK, Roselaar CSK, van Brandwijk H, Nijman V, Vonk R (2013) DNA barcoding of dutch birds. Zookeys 365:25–48. https://doi.org/10.3897/zookeys.365.6287
Awad A, Khalil SR, Abd-Elhakim YM (2014) Molecular phylogeny of some avian species using cytochrome b gene sequence analysis. Iran J Vet Res 162:218–222. https://doi.org/10.22099/IJVR.2015.3072
Bildstein KL, Schelsky W, Zalles J, Ellis S (1998) Conservation status of tropical raptors. J Raptor Res 32:3–18
Breman FC, Jordaens K, Sonet G, Nagy ZT, Van Houdt J, Louette M (2012) DNA barcoding and evolutionary relationships in Accipiter Brisson, 1760 (Aves, Falconiformes: Accipitridae) with a focus on African and Eurasian representatives. J Ornithol 154:265–287. https://doi.org/10.1007/s10336-012-0892-5
Bridge PD, Roberts PJ, Spooner BM, Panchal G (2003) On the unreliability of published DNA sequences. New Phytol 160:43–48. https://doi.org/10.1046/j.1469-8137.2003.00861.x
Brown SD, Collins RA, Boyer S, Lefort MC, Malumbres-Olarte J, Vink CJ, Cruickshank RH (2012) Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding. Mol Ecol Resour 12:562–565. https://doi.org/10.1111/j.1755-0998.2011.03108.x
Cai Y, Yue B, Jiang W, **e S, Li J, Zhou M (2010) DNA barcoding on subsets of three families in Aves DNA barcoding on subsets of three families in Aves. Mitochondrial DNA 21:132–137. https://doi.org/10.3109/19401736.2010.494726
Chalermwong P, Panthum T, Wattanadilokcahtkun P, Ariyaraphong N, Thong T, Srikampa P, Singchat W, Ahmad SF, Noito K, Rasoarahona R, Lisachov A, Ali H, Kraichak E, Muangmai N, Chatchaiphan S, Sriphairoj K, Hatachote S, Chaiyes A, Jantasuriyarat C, Chailertlit V, Suksavate W, Sonongbua J, Witsanu Srimai W, Payungporn S, Han K, Antunes A, Srisapoome P, Koga A, Duengkae P, Matsuda Y, Na-Nakorn U, Srikulnath K (2023) Overcoming taxonomic challenges in DNA barcoding for improvement of identification and preservation or conservation of clariid catfish species. Genom Inform 21:339
Chaves BRN, Chaves AV, Nascimento ACA, Chevitarese J, Vasconcelos MF, Santos FR (2014) Barcoding neotropical birds: assessing the impact of nonmonophyly in a highly diverse group. Mol Ecol Resour 15:921–931. https://doi.org/10.1111/1755-0998.12344
Colihueque N, Gantz A, Rau JR, Parraguez M (2015) Genetic divergence analysis of the common barn owl Tyto alba (Scopoli, 1769) and the short-eared owl Asio flammeus (Pontoppidan, 1763) from southern Chile using COI sequence. ZooKeys 2015:135–146. https://doi.org/10.3897/zookeys.534.5953
Delrieu-Trottin E, Durand JD, Limmon G, Sukmono T, Kadarusman SHY, Chen WJ, Busson F, Borsa P, Dahruddin H, Sauri S, Fitriana Y, Zein MSA, Hocdé R, Pouyaud L, Keith P, Wowor D, Steinke D, Hanner R, Hubert N (2020) Biodiversity inventory of the grey mullets (Actinopterygii: Mugilidae) of the Indo-Australian archipelago through the iterative use of DNA-based species delimitation and specimen assignment methods. Evol Appl 13:1451–1467. https://doi.org/10.1111/eva.12926
Dove CJ, Rotzel NC, Heacker M, Weigt LA (2008) Using DNA barcodes to identify bird species involved in birdstrikes. J Wildl Manag 72:1231–1236. https://doi.org/10.2193/2007-272
Efe MA, Tavares ES, Baker AJ, Bonatto SL (2009) Multigene phylogeny and DNA barcoding indicate that the sandwich tern complex (Thalasseus sandvicensis, Laridae, Sternini) comprises two species. Mol Phylogenetics Evol 52:263–267. https://doi.org/10.1016/j.ympev.2009.03.030
Eo SH, DeWoody JA (2010) Evolutionary rates of mitochondrial genomes correspond to diversification rates and to contemporary species richness in birds and reptiles. ProcR Soc b: Biol Sci 277:3587–3592. https://doi.org/10.1098/rspb.2010.0965
Erixon P, Svennblad B, Britton T, Oxelman B (2003) Reliability of Bayesian posterior probabilities and bootstrap frequencies in phylogenetics. Syst Biol 52:665–673. https://doi.org/10.1080/10635150390235485
Fang H, Liu X, Shao X, **n F, Wang B, Wang M, Jiang K, Liu M, Wang L (2020) Molecular and functional characterization of Raptor in mTOR pathway from Litopenaeus vannamei. Aquac Res 51:2179–2189. https://doi.org/10.1111/are.14522
Felsenstein J (1984) Distance methods for inferring phylogenies: a justification. Evolution 38:16–24. https://doi.org/10.2307/2408542
Fowler DW, Freedman EA, Scannella JB (2009) Predatory functional morphology in raptors: interdigital variation in talon size is related to prey restraint and immobilisation technique. PLoS ONE 4:e7999. https://doi.org/10.7934/p268
Gamauf A, Haring E (2004) Molecular phylogeny and biogeography of Honey-buzzards (genera Pernis and Henicopernis). J Zool Syst Evol Res 42:145–153. https://doi.org/10.1111/j.1439-0469.2004.00250.x
Ganbold O, Bing GC, Munkhbayar M, Paek WK, Purevee E, Jargal N, Oyunbat R, Jargalsaikhan A (2020) Low genetic variation of cinereous vultures (Aegypius monachus) revealed by the mitochondrial COI gene in central Mongolia. J Asia-Pac Biodivers 14:93–97. https://doi.org/10.1016/j.japb.2020.09.010
Garbett R, Maude G, Hancock P, Kenny D, Reading R, Amar A (2018) Association between hunting and elevated blood lead levels in the critically endangered African white-backed vulture Gyps africanus. Sci Total Environ 630:1654–1665. https://doi.org/10.1016/j.scitotenv.2018.02.220
Gjershaug JO, Diserud OH, Kleven O, Rasmussen PC, Espmark Y (2020) Integrative taxonomy of the changeable hawk-eagle Nisaetus cirrhatus complex (Accipitriformes: Accipitridae) in India. Zootaxa 4789:554–574. https://doi.org/10.11646/zootaxa.4789.2.10
Griffiths CS, Barrowclough GF, Groth JG, Mertz L (2004) Phylogeny of the Falconidae (aves): a comparison of the efficacy of morphological, mitochondrial, and nuclear data. Mol Phylogenet Evol 32:101–109. https://doi.org/10.1016/j.ympev.2003.11.019
Han SH, Oh HS (2016) Genetic identification for prey birds of the endangered peregrine falcon (Falco peregrinus). Mitochondrial DNA A DNA Mapp Seq Anal 29:175–180. https://doi.org/10.1080/24701394.2016.1261853
Haring E, Kruckenhauser L, Gamauf A, Riesing MJ, Pinsker W (2001) The complete sequence of the mitochondrial genome of Buteo buteo (Aves, Accipitridae) indicates an early split in the phylogeny of raptors. Mol Biol Evol 18:1892–1904. https://doi.org/10.1093/oxfordjournals.molbev.a003730
Hebert PD, Cywinska A, Ball SL, deWaard JR (2003) Biological identifications through DNA barcodes. Proc Biol Sci 270:313–321. https://doi.org/10.1098/rspb.2002.2218
Hebert PDN, Stoeckle MY, Zemlak TS, Francis CM (2004) Identification of birds through DNA barcodes. PLoS Biol 2:e312. https://doi.org/10.1371/journal.pbio.0020312
Hellgren O, Križanauskiene A, Valkiunas G, Bensch S (2007) Diversity and phylogeny of mitochondrial cytochrome b lineages from six morphospecies of avian Haemoproteus (Haemosporida: Haemoproteidae). J Parasitol 93:889–896. https://doi.org/10.1645/ge-1051r1.1
Iknayan KJ, Beissinger SR (2018) Collapse of a desert bird community over the past century driven by climate change. Proc Natl Acad Sci USA 115:8597–8602. https://doi.org/10.5070/p536146409
Ingram J, Woodward I (2003) Welcome to new editors development, eco-devo and environmental adaptation. New Phytol 160:1–2. https://doi.org/10.1046/j.1469-8137.2003.00891.x
IUCN (2022) The IUCN Red List of Threatened Species. Version 2022-2. https://www.iucnredlist.org. Accessed on 11 May 2022
Jaonalison H, Durand JD, Mahafina J, Valade P, Collet A, Cerqueira F, Ponton D (2022) Application of DNA barcoding for monitoring Madagascar fish biodiversity in coastal areas. Diversity 14:377. https://doi.org/10.3390/d14050377
** S, Paik I, Lee S, Han G, Yu J, Paek W (2014) DNA barcoding of raptor carcass collected in the Paju City, Korea. Korean J Environ Ecol 28:523–530. https://doi.org/10.13047/kjee.2014.28.5.523
Johnsen A, Rindal E, Ericson PGP, Zuccon D, Kerr KCR, Stoeckle MY, Lifjeld JT (2010) DNA barcoding of Scandinavian birds reveals divergent lineages in trans-Atlantic species. J Ornithol 151:565–578. https://doi.org/10.1007/s10336-009-0490-3
Johnson JA, Lerner HRL, Rasmussen PC, Mindell DP (2006) Systematics within Gyps vultures: a clade at risk. BMC Evol Biol 6:1–12. https://doi.org/10.1186/1471-2148-6-65
Kerr KCR, Stoeckle MY, Dove CJ, Weigt LA, Francis CM, Hebert PDN (2006) Comprehensive DNA barcode coverage of North American birds. Mol Ecol Notes 7:535–543. https://doi.org/10.1111/j.1471-8286.2007.01670.x
Kerr KCR, Lijtmaer DA, Barreira AS, Hebert PDN, Tubaro PL (2008) Probing evolutionary patterns in neotropical birds through DNA barcodes. PLoS ONE 4:e4379. https://doi.org/10.1371/journal.pone.0004379
Kim J, Do TD, Lee D, Yeo Y, Kim CB (2020) Application of cytochrome b gene sequences for identification of parrots from Korean zoos. Anim Syst Evol Divers 36:216–221. https://doi.org/10.11626/kjeb.2020.38.3.350
Koonin EV (2003) Comparative genomics, minimal gene-sets and the last universal common ancestor. Nat Rev Microbiol 1:127–136. https://doi.org/10.1038/nrmicro751
Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: molecular evolutionary genetics analysis across computing plat forms. Mol Biol Evol 35:1547. https://doi.org/10.1093/molbev/msy096
Lee JCI, Tsai LC, Huang MT, Jhuang JA, Yao CT, Chin SC, Wang LC, Linacre A, Hsieh HM (2008) A novel strategy for avian species identification by cytochrome b gene. Electrophoresis 29:2413–2418. https://doi.org/10.1002/elps.200700711
Lerner HRL, Mindell DP (2005) Phylogeny of eagles, Old World vultures, and other Accipitridae based on nuclear and mitochondrial DNA. Mol Phylogenet Evol 37:327–346. https://doi.org/10.1016/j.ympev.2005.04.010
Lerner HRL, Klaver MC, Mindell DP (2007) Molecular phylogenetics of the buteonine birds of prey (Accipitridae). Auk 125:304–315. https://doi.org/10.1525/auk.2008.06161
Liang X, Liu M, Ying C, Zhang Z (2022) Myological variation in the hindlimb of three raptorial birds in relation to foraging behavior. Avian Res 13:100053. https://doi.org/10.1016/j.avrs.2022.100053
Limparungpatthanakij W, Nualsri C, Jearwattanakanok A, Hansasuta C, Sutasha K, Angkaew R, Round P (2020) Abundance and timing of migratory raptors passing through Khao Dinsor, Southern Thailand, in autumn 2015–2016. J Asian Ornithol 35:18–27
Luo A, Zhang A, Ho SYW, Xu W, Zhang Y, Shi W, Cameron SL, Zhu C (2011) Potential efficacy of mitochondrial genes for animal DNA barcoding: a case study using eutherian mammals. BMC Genom 12:84. https://doi.org/10.1186/1471-2164-12-84
Markandya A, Taylor T, Longo A, Murty MN, Murty S, Dhavala K (2008) Counting the cost of vulture decline an appraisal of the human health and other benefits of vultures in India. Ecol Econ 67:194–204. https://doi.org/10.1016/j.ecolecon.2008.04.020
Matumba TG, Oliver J, Barker NP, McQuaid CD, Teske PR (2020) Intraspecific mitochondrial gene variation can be as low as that of nuclear rRNA. F1000Res 9:1–16. https://doi.org/10.12688/f1000research.23635.1
McClure CJW, Westrip JRS, Johnson JA, Schulwitz SE, Virani MZ, Davies R, Symes A, Wheatley H, Thorstrom R, Amar A, Buij R, Jones VR, Williams NP, Buechley ER, Butchart SHM (2018) State of the world’s raptors: distributions, threats, and conservation recommendations. Biol Conserv 227:390–402. https://doi.org/10.1016/j.biocon.2018.08.012
Meier R, Shiyang K, Vaidya G, Ng PK (2006) DNA barcoding and taxonomy in Diptera: a tale of high intraspecific variability and low identification success. Syst Biol 55:715–728. https://doi.org/10.1080/10635150600969864
Mindell DP, Sorenson MD, Huddleston CJ, Miranda HC, Knight A, Sawchuk SJ, Yuri T (1997) Phylogenetic relationships among and within select avian orders based on mitochondrial DNA. Avian Mol Evol Syst 2019:213–247. https://doi.org/10.1016/b978-012498315-1/50014-5
Mojica EK, Dwyer JF, Harness RE, Williams GE, Woodbridge B (2018) Review and synthesis of research investigating golden eagle electrocutions. J Wildl Manag 82:495–506. https://doi.org/10.1002/jwmg.21412
Nagy J, Tökölyi J (2014) Phylogeny, historical biogeography and the evolution of migration in accipitrid birds of prey (Aves: Accipitriformes). Ornis Hung 22:15–35. https://doi.org/10.2478/orhu-2014-0008
Ong PS, Luczon AU, Quilang JP, Sumaya AMT, Ibañez JC, Salvador DJ, Fontanilla IKC (2011) DNA barcodes of Philippine accipitrids. Mol Ecol Resour 11:245–254. https://doi.org/10.1111/j.1755-0998.2010.02928.x
Pain ADJ, Cunningham AA, Donald PF, Duckworth JW, Houston DC, Poole C, Prakash V, Round A, Timmins R (2003) Causes and effects of temporospatial declines of Gyps vultures in Asia. Conserv Biol 17:661–671. https://doi.org/10.1046/j.1523-1739.2003.01740.x
Panter CT, White RL (2020) Insights from social media into the illegal trade of wild raptors in Thailand. TRAFFIC Bull 32:5–12
Panthum T, Ariyaphong N, Wattanadilokchatkun P, Singchat W, Ahmad SF, Kraichak E, Dokkaew S, Muangmai N, Han K, Duengkae P, Srikulnath K (2022) Quality control of fighting fish nucleotide sequences in public repositories reveals a dark matter of systematic taxonomic implication. Genes Genom 45:169–181. https://doi.org/10.1007/s13258-022-01353-7
Papadopoulou A, Bergsten J, Fujisawa T, Monaghan MT, Barraclough TG, Vogler AP (2008) Speciation and DNA barcodes: testing the effects of dispersal on the formation of discrete sequence clusters. Philos Trans R Soc b: Biol Sci 363:2987–2996. https://doi.org/10.1098/rstb.2008.0066
Paradis E, Claude J, Strimmer K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20:289–290. https://doi.org/10.1093/bioinformatics/btg412
Parson W, Pegoraro K, Niederstätter H, Föger M, Steinlechner M (2000) Species identification by means of the cytochrome b gene. Int J Leg Med 114:23–28. https://doi.org/10.1007/s004140000134
Peona V, Blom MPK, Xu L, Burri R, Sullivan S, Bunikis I, Liachko I, Haryoko T, Jønsson KA, Zhou Q, Irestedt M, Suh A (2021) Identifying the causes and consequences of assembly gaps using a multiplatform genome assembly of a bird-of-paradise. Mol Ecol Resour 21:263–286. https://doi.org/10.1111/1755-0998.13252
Philippe H, De Vienne DM, Ranwez V, Roure B, Baurain D, Delsuc F (2017) Pitfalls in supermatrix phylogenomics. Eur J Taxon 283:1–25. https://doi.org/10.5852/ejt.2017.283
Pons J, Barraclough TG, Gomez-Zurita J, Cardoso A, Duran DP, Hazell S, Kamoun S, Sumlin WD, Vogler AP (2006) Sequence based species delimitation for the DNA taxonomy of undescribed insects. Syst Biol 55:595–609. https://doi.org/10.1080/10635150600852011
Quek MC, Chin NL, Tan SW, Yusof YA, Law CL (2018) Molecular identification of species and production origins of edible bird’s nest using FINS and SYBR green I based real-time PCR. Food Control 84:118–127. https://doi.org/10.1016/j.foodcont.2017.07.027
R Core Team (2022) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
Remsen JV, Jr JI, Areta E, Bonaccorso S, Claramunt G, Del-Rio A, Jaramillo DF, Lane MB, Robbins FG, Stiles, Zimmer KJ Version (2023) A classification of the bird species of South America. Museum of Natural Science, Louisiana State University. http://www.museum.lsu.edu/~Remsen/SACCBaseline.htm
Ronquist F, Teslenko M, Van Der Mark P, Ayres DL, Darling A, Höhna S, Larget B, Liu L, Suchard MA, Huelsenbeck JP (2012) MrBayes3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol 61:539–542. https://doi.org/10.1093/sysbio/sys029
Ryan PG, Bloomer P (1999) The long-billed lark complex: a species mosaic in southwestern Africa. Auk 116:194–208. https://doi.org/10.2307/4089466
Saitoh T, Sugita N, Someya S, Iwami Y, Kobayashi S, Kamigaichi H, Higuchi A, Asai S, Yamamoto Y, Nishiumi I (2015) DNA barcoding reveals 24 distinct lineages as cryptic bird species candidates in and around the Japanese archipelago. Mol Ecoc Resour 15:177–186. https://doi.org/10.1111/1755-0998.12282
Sarasola JH, Grande JM, Negro JJ (2018) Birds of prey: biology and conservation in the XXI century. Springer International Publishing, Cham, Switzerland
Sehgal RNM, Hull AC, Anderson NL, Valkiunas G, Markovets MJ, Kawamura S, Tell LA (2005) Evidence for cryptic speciation of Leucocytozoon spp. (Haemosporida, Leucocytozoidae) in diurnal raptors. J Parasitol 92:375–379. https://doi.org/10.1645/ge-656r.1
Shen YY, Chen X, Murphy RW (2013) Assessing DNA barcoding as a tool for species identification and data quality control. PLoS ONE 8:1–5. https://doi.org/10.1371/journal.pone.0057125
Siriwat P, Nijman V (2020) Wildlife trade shifts from brick-and-mortar markets to virtual marketplaces: a case study of birds of prey trade in Thailand. J Asia-Pac Biodivers 13:454–461. https://doi.org/10.1016/j.japb.2020.03.012
Starikov IJ, Wink M (2020) Old and cosmopolite: molecular phylogeny of tropical–subtropical kites (Aves: Elaninae) with taxonomic implications. Diversity 12:327. https://doi.org/10.3390/d12090327
Supikamolseni A, Ngaoburanawit N, Sumontha M, Chanhome L, Suntrarachun S, Peyachoknagul S, Srikulnath K (2015) Molecular barcoding of venomous snakes and species-specific multiplex PCR assay to identify snake groups for which antivenom is available in Thailand. Genet Mol Res 14:13981–13997. https://doi.org/10.4238/2015.october.29.18
Tavares ES, Gonçalves P, Miyaki CY, Baker AJ (2011) DNA barcode detects high genetic structure within neotropical bird species. PLoS ONE 6:e28543. https://doi.org/10.1371/journal.pone.0028543
Tizard J, Patel S, Waugh J, Tavares E, Bergmann T, Gill B, Norman J, Christidis L, Scofield P, Haddrath O, Baker A, Lambert D, Millar C (2019) DNA barcoding a unique avifauna: an important tool for evolution, systematics and conservation. BMC Evol Biol 19:1–13. https://doi.org/10.1186/s12862-019-1346-y
Vogler AP, Monaghan MT (2007) Recent advances in DNA taxonomy. J Zool Syst Evol Res 45:1–10. https://doi.org/10.1111/j.1439-0469.2006.00384.x
Waugh J (2007) DNA barcoding in animal species: progress, potential and pitfalls. BioEssays 29:188–197. https://doi.org/10.1002/bies.20529
Wink M (1995) Phylogeny of old and new world vultures (aves: Accipitridae and Cathartidae) inferred from nucleotide sequences of the mitochondrial cytochrome b gene. Z Fur Naturforsch C J Biosci 50:868–882. https://doi.org/10.1515/znc-1995-11-1220
Wu Y, Yan Y, Zhao Y, Gu L, Wang S, Johnson DH (2021) Genomic bases underlying the adaptive radiation of core landbirds. BMC Ecol Evol 21:162. https://doi.org/10.1101/2020.07.29.222281
**a X (2018) DAMBE7: New and improved tools for data analysis in molecular biology and evolution. Mol Biol Evol 35:1550–1552. https://doi.org/10.1093/molbev/msy073
**a X, Lemey P (2009) Assessing substitution saturation with DAMBE. In: Lemey P, Salemi M, Vandamme A-M (eds) The phylogenetic handbook: a practical approach to DNA and protein phylogeny, vol 2. Cambridge University Press, Cambridge, pp 615–630. https://doi.org/10.1017/cbo9780511819049.022
**a X, **e Z, Salemi M, Chen L, Wang Y (2003) An index of substitution saturation and its application. Mol Phylogenet Evol 26:1–7. https://doi.org/10.1016/s1055-7903(02)00326-3
Zhang J, Kapli P, Pavlidis P, Stamatakis A (2013) A general species delimitation method with applications to phylogenetic placements. Bioinform 29:2869–2876. https://doi.org/10.1093/bioinformatics/btt499
Acknowledgements
We wish to thank the public data repository for supplying accession numbers to the raptors. We also wish to thank the Faculty of Veterinary Medicine and the Faculty of Science, Kasetsart University and the Center for Bio-Medical Engineering Core Facility, Dankook University for providing supporting research facilities. This research was financially supported in part by the Graduate grants scholarship of the Faculty of Science, Kasetsart University (6417400239) grant awarded to JS, a Thailand Science Research and Innovation grant through the Kasetsart University Reinventing University Program 2021 (3/2564) awarded to TP and KS, the High-Quality Research Graduate Development Cooperation Project between Kasetsart University and the National Science and Technology Development Agency awarded to TP and KS, and the Higher Education for Industry Consortium (Hi-FI) (6514400931 and 6414400777) awarded to WJ and NA.
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Contributions
Conceptualization: WJ, JS, and KS. Data curation: WJ, JS, TP, and KS. Formal analysis: WJ, JS, TP, PW, NA, WS, SFA, and KS. Funding acquisition: KS. Investigation: WJ and JS. Methodology: WJ, JS, TP, and KS. Project administration: KS. Visualization: NM, PD, CK, and KS. Writing—original draft: WJ, JS, and KS. Writing—review and editing: WJ, JS, TP, PW, NA, TT, WS, SFA, EK, NM, KH, AA, RS, AK, PD, CK, and KS. All authors have read and agreed to the published version of the manuscript.
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The authors declare no competing financial interests or personal relationships that influenced this study.
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All animal care and experimental procedures were approved by the Animal Experiment Committee of Kasetsart University, Thailand (Approval No. ACKU64-VET-002 and ACKU64-VET-052) and conducted in accordance with the Regulations on Animal Experiments at Kasetsart University.
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Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary Fig. 1
A cladogram clarifying the phylogenetic relationships among the 889 GenBank accessions was constructed from a Bayesian inference analysis using mitochondrial cytochrome c oxidase I (COI) sequences. The bPTP model highlights species with an orange hue, the GMYC model with green, and overlap** indications are represented in black (DOCX 300 KB)
Supplementary Fig. 2
A cladogram clarifying the phylogenetic relationships among the 1,062 GenBank accessions was constructed from a Bayesian inference analysis using mitochondrial cytochrome b (Cytb) sequences. The bPTP model highlights species with an orange hue, the GMYC model with green, and overlap** indications are represented in black (DOCX 276 KB)
Supplementary Fig. 3
A cladogram clarifying the phylogenetic relationships among the collected sample sequences from eight species was constructed from a Bayesian inference analysis using cytochrome c oxidase I (COI) sequences. The common kestrel (Falco tinnunculus) was identified as an outgroup (DOCX 123 KB)
Supplementary Fig. 4
A cladogram clarifying the phylogenetic relationships among the collected sample sequences from eight species was constructed from a Bayesian inference analysis using mitochondrial cytochrome b (Cytb) sequences. The common kestrel (Falco tinnunculus) was identified as an outgroup (DOCX 124 KB)
Supplementary Fig. 5
A cladogram clarifying the phylogenetic relationships among the 889 GenBank accessions was constructed from the Bayesian inference analysis using mitochondrial cytochrome c oxidase I (COI) sequences. Group 1: higher-level similarity with the same species. Group 2: higher-level similarity with multiple species. Group 3: unique sequences with no similarity within most sequences. Class 1: sequences with the same species name exhibiting intraspecific cohesive clustering and interspecific distinct clustering with high posterior probability (0.90–1.00). Class 2: sequences with the same species name that do not exhibit intraspecific cohesive clustering. Class 3: sequences with a different species name exhibiting cohesive clustering (DOCX 298 KB)
Supplementary Fig. 6
A cladogram clarifying the phylogenetic relationships among the 1062 GenBank accessions was constructed from Bayesian inference analysis using mitochondrial cytochrome b (Cytb) sequences. Group 1: higher-level similarity with the same species. Group 2: higher-level similarity with multiple species. Group 3: unique sequences with no similarity within most sequences. Class 1: sequences with the same species name exhibiting intraspecific cohesive clustering and interspecific distinct clustering with high posterior probability (0.90–1.00). Class 2: sequences with the same species name that do not exhibit intraspecific cohesive clustering. Class 3: sequences with a different species name exhibiting cohesive clustering (DOCX 251 KB)
Supplementary Fig. 7
A cladogram clarifying the phylogenetic relationships among the eight species from collected samples were constructed from Bayesian inference analysis using mitochondrial cytochrome c oxidase I (COI) sequences. The common kestrel (Falco tinnunculus) was identified as an outgroup. Group 1: higher-level similarity with the same species. Class 1: sequences with the same species name exhibiting intraspecific cohesive clustering and interspecific distinct clustering with high posterior probability (0.90–1.00) (DOCX 113 KB)
Supplementary Fig. 8
A cladogram clarifying the phylogenetic relationships among the collected sample sequences eight species was constructed from Bayesian inference analysis using mitochondrial cytochrome b (Cytb) sequences. The common kestrel (Falco tinnunculus) was identified as an outgroup. Group 1: higher-level similarity with the same species. Class 1: sequences with the same species name exhibiting intraspecific cohesive clustering and interspecific distinct clustering with high posterior probability (0.90–1.00) (DOCX 121 KB)
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Jaito, W., Sonongbua, J., Panthum, T. et al. Disclosing the hidden nucleotide sequences: a journey into DNA barcoding of raptor species in public repositories. Genes Genom 46, 95–112 (2024). https://doi.org/10.1007/s13258-023-01462-x
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DOI: https://doi.org/10.1007/s13258-023-01462-x