in

Environmental DNA reveals the distinct genetic diversity and evolutionary pathways of the Chinese Minnow Rhynchocypris oxycephalus in Korean freshwater systems


Abstract

Establishing an environmental DNA (eDNA) reference library at regional and local scales is essential not only for accurate biodiversity assessment but also for comprehensive long-term monitoring. To date, genetic diversity studies of the Chinese minnow (Rhynchocypris oxycephalus) have largely been restricted to China, leaving substantial knowledge gaps across its broader distribution, including South Korea. Hence, the present study identified suitable regions for guiding eDNA surveys and non-invasive sampling, based on documented occurrences retrieved from the IUCN Geospatial Conservation Assessment Tool (GeoCAT). The newly designed primer pairs successfully amplified long mitochondrial fragments (~ 1 kb) of the cytochrome b (Cytb) and 16S ribosomal RNA (16S rRNA) genes. The generated sequences revealed 29 haplotypes from 41 Cytb sequences and 13 haplotypes from 21 16S rRNA sequences, corresponding to high intraspecific genetic diversity (5.57% for Cytb and 2.46% for 16S rRNA), thereby indicating potential cryptic diversity of R. oxycephalus in South Korea. The phylogenetic analyses, combined with multiple species delimitation methods, resolved several putative molecular operational taxonomic units and highlighted a distinct genetic clade in the Seomjin River basin, likely driven by microhabitat-specific evolutionary processes. In addition, the shared haplotypes across catchments of different river basins indicate either ongoing gene flow or anthropogenic influences contributing to genetic admixture of R. oxycephalus. The time-calibrated phylogenetic analyses also suggest that historical geographic changes and ancient river networks, from the Early Miocene to the Late Pliocene, likely facilitated the diversification of R. oxycephalus across China, the Korean Peninsula, and Japan. Overall, this study represents the first eDNA-based assessment of R. oxycephalus diversity in South Korea, while also providing new evolutionary insights from a broader geographic context in China and Japan. Given the complexity of multiple river networks in South Korea, further investigations using multiple genetic markers are recommended to enhance understanding of this cyprinid species phylogeography in the region.

Similar content being viewed by others

Three genome assemblies of Opsariichthys bidens from Yangzte River, Pearl River and Qiantang River basins

Genetic pattern and demographic history of cutlassfish (Trichiurus nanhaiensis) in South China Sea by the influence of Pleistocene climatic oscillations

Population structure and genetic diversity of the endangered fish black shinner Pseudopungtungia nigra (Cyprinidae) in Korea: a wild and restoration population

Data availability

The generated sequencing data has been deposited in NCBI GenBank (https://www.ncbi.nlm.nih.gov/) with the following accession numbers PQ330261 to PQ330301 and PQ333020 to PQ333040.

References

  1. Karr, J. R. Assessment of biotic integrity using fish communities. Fisheries 6, 21–27. https://doi.org/10.1577/1548-8446(1981)006%3C0021:AOBIUF%3E2.0.CO;2 (1981).

    Google Scholar 

  2. Reynolds, J. D., Dulvy, N. K., Goodwin, N. B. & Hutchings, J. A. Biology of extinction risk in marine fishes. Proc. R Soc. B-Biol Sci. 272, 2337–2344. https://doi.org/10.1098/rspb.2005.3281 (2005).

    Google Scholar 

  3. Dudgeon, D. et al. Freshwater biodiversity: importance, threats, status and conservation challenges. Biol. Rev. 81, 163–182. https://doi.org/10.1017/S1464793105006950 (2006).

    Google Scholar 

  4. Jackson, D. A., Peres-Neto, P. R. & Olden, J. D. What controls who is where in freshwater fish communities the roles of biotic, abiotic, and Spatial factors. Can. J. Fish. Aquat. Sci. 58, 157–170. https://doi.org/10.1139/f00-239 (2001).

    Google Scholar 

  5. Bonar, S. A., Hubert, W. A. & Willis, D. W. Standard Methods for Sampling North American Freshwater Fishes (American Fisheries Society, 2009).

  6. Deng, J. et al. eDNA metabarcoding reveals differences in fish diversity and community structure in Danjiang river. Sci. Rep. 14, 29460. https://doi.org/10.1038/s41598-024-80907-z (2024).

    Google Scholar 

  7. Deiner, K. et al. Environmental DNA metabarcoding: transforming how we survey animal and plant communities. Mol. Ecol. 26, 5872–5895. https://doi.org/10.1111/mec.14350 (2017).

    Google Scholar 

  8. Thomsen, P. F. et al. Detection of a diverse marine fish fauna using environmental DNA from seawater samples. PLoS One. 7, e41732. https://doi.org/10.1371/journal.pone.0041732 (2012).

    Google Scholar 

  9. Goldberg, C. S. et al. Critical considerations for the application of environmental DNA methods to detect aquatic species. Methods Ecol. Evol. 7, 1299–1307. https://doi.org/10.1111/2041-210X.12595 (2016).

    Google Scholar 

  10. Evans, N. T. Fish community assessment with eDNA metabarcoding: effects of sampling design and bioinformatic filtering. Can. J. Fish. Aquat. Sci. 74, 1362–1374. https://doi.org/10.1139/cjfas-2016-0306 (2017).

    Google Scholar 

  11. Jerde, C. L., Mahon, A. R., Chadderton, W. L. & Lodge, D. M. Sight-unseen detection of rare aquatic species using environmental DNA. Conserv. Lett. 4, 150–157. https://doi.org/10.1111/j.1755-263X.2010.00158.x (2011).

    Google Scholar 

  12. Bista, I. et al. Annual time-series analysis of aqueous eDNA reveals ecologically relevant dynamics of lake ecosystem biodiversity. Nat. Commun. 8, 14087. https://doi.org/10.1038/ncomms14087 (2017).

    Google Scholar 

  13. Valentini, A. et al. Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Mol. Ecol. 25, 929–942. https://doi.org/10.1111/mec.13428 (2016).

    Google Scholar 

  14. Hubert, N. & Hanner, R. DNA barcoding, species delineation and taxonomy: a historical perspective. DNA Barcodes. 3, 44–58 (2015). https://hal.science/hal-01958691

    Google Scholar 

  15. Bernatchez, L. & Wilson, C. C. Comparative phylogeography of Nearctic and Palearctic fishes. Mol. Ecol. 7, 431–452. https://doi.org/10.1046/j.1365-294x.1998.00319.x (1998).

    Google Scholar 

  16. Bogutskaya, N. Rhynchocypris oxycephalus. The IUCN Red List of Threatened Species e.T159709916A159709987 (2022). https://doi.org/10.2305/IUCN.UK.2022-1.RLTS.T159709916A159709987.en (2022).

  17. Xu, W., Chen, A., Xia, R. & Fu, C. Complete mitochondrial genome of Rhynchocypris cf. lagowskii (Cypriniformes: Cyprinidae). Mitochondrial DNA. 25, 379–380. https://doi.org/10.3109/19401736.2013.809432 (2014).

    Google Scholar 

  18. Yu, D., Chen, M., Tang, Q., Li, X. & Liu, H. Geological events and pliocene climate fluctuations explain the phylogeographical pattern of the cold water fish Rhynchocypris oxycephalus (Cypriniformes: Cyprinidae) in China. BMC Evol. Biol. 14, 1–12. https://doi.org/10.1186/s12862-014-0225-9 (2014).

    Google Scholar 

  19. Jang, M. H., Lucas, M. C. & Joo, G. J. The fish fauna of mountain streams in South Korean National parks and its significance to conservation of regional freshwater fish biodiversity. Biol. Conserv. 114, 115–126. https://doi.org/10.1016/S0006-3207(03)00016-8 (2003).

    Google Scholar 

  20. Bogutskaya, N. G., Naseka, A. M., Shedko, S. V., Vasileva, E. D. & Chereschnev, I. A. The fishes of the Amur river: updated check-list and zoogeography. Ichthyol. Explor. Freshw. 19, 301–366 (2008).

    Google Scholar 

  21. Jang, M. H. et al. The current status of the distribution of introduced fish in large river systems of South Korea. Int. Rev. Hydrobiol. 87, 319–328. https://doi.org/10.1002/1522-2632(200205)87:2/3%3C319::AID-IROH319%3E3.0.CO;2-N (2002).

    Google Scholar 

  22. Liang, Y., Sui, X., Chen, Y., Jia, Y. & He, D. Life history traits of the Chinese minnow Rhynchocypris oxycephalus in the upper branch of Yangtze River, China. Zool. Stud. 53, 1–10. https://doi.org/10.1186/s40555-014-0036-0 (2014).

    Google Scholar 

  23. Park, J., Kim, Y. & Xi, H. The complete mitochondrial genome sequence of Chinese minnow in Korea, Rhynchocypris oxycephalus (Sauvage and Dabry de Thiersant, 1874). Mitochondrial DNA Part. B-Resour. 4, 662–663. https://doi.org/10.1080/23802359.2019.1572472 (2019).

    Google Scholar 

  24. Yu, D. et al. Global climate change will severely decrease potential distribution of the East Asian Coldwater fish Rhynchocypris oxycephalus. Cyprinidae) Hydrobiologia. 700, 23–32. https://doi.org/10.1007/s10750-012-1213-y (2013). Actinopterygii.

    Google Scholar 

  25. Sakai, H. et al. Phylogenetic and taxonomic relationships of Northern Far Eastern Phoxinin minnows, Phoxinus and Rhynchocypris (Pisces, Cyprinidae), as inferred from allozyme and mitochondrial 16S rRNA sequence analyses. Zool. Sci. 23, 323–331. https://doi.org/10.2108/zsj.23.323 (2006).

    Google Scholar 

  26. Yang, S. & Min, M. Sympatry and species status of Moroco lagowskii and M. oxycephalus (Cyprinidae). Korean J. Zool. 31, 56–61 (1988).

    Google Scholar 

  27. Zhang, Z., Cheng, Q. & Ge, Y. The complete mitochondrial genome of Rhynchocypris oxycephalus (Teleostei: Cyprinidae) and its phylogenetic implications. Ecol. Evol. 9, 7819–7837. https://doi.org/10.1002/ece3.5369 (2019).

    Google Scholar 

  28. Takai, N. et al. Species identification of upstream fatminnow Rhynchocypris oxycephalus and downstream fatminnow Rhynchocypris lagowskii, based on PCR-RFLP of mitochondrial DNA. Ichthyol. Res. 59, 156–163. https://doi.org/10.1007/s10228-011-0266-7 (2012).

    Google Scholar 

  29. Nishida, K. et al. Genetic evidence of the native Easternmost distribution limit of Rhynchocypris oxycephala (Actinopterygii: Cypriniformes) and its introduction to rivers in Eastern Japan, based on mitochondrial DNA D-loop analysis. Biogeography 25, 45–54. https://doi.org/10.11358/biogeo.25.45 (2023).

    Google Scholar 

  30. Sui, X., Liang, Y. & He, D. The complete mitochondrial genome of Rhynchocypris oxycephalus (Cypriniformes: Cyprinidae). Mitochondrial DNA Part. A. 27, 3367–3369. https://doi.org/10.3109/19401736.2015.1018224 (2016).

    Google Scholar 

  31. Min, M. & Yang, S. Morphology and distribution of Moroco percnurus (Cyprinidae). Korean J. Zool. 35, 508 (1992).

    Google Scholar 

  32. Park, I. S., Choi, Y., Kim, Y. H., Nam, Y. K. & Kim, D. S. Flow cytometric and cytogenetic studies in Rhynchocypris oxycephalus and R. steindachneri. J. Aquaculture. 13, 193–196 (2000).

    Google Scholar 

  33. Miya, M. et al. MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species. R Soc. Open. Sci. 2, 150088. https://doi.org/10.1098/rsos.150088 (2015).

    Google Scholar 

  34. Alam, M. J. et al. Assessment of fish biodiversity in four Korean rivers using environmental DNA metabarcoding. PeerJ 8, e9508. https://doi.org/10.7717/peerj.9508 (2020).

    Google Scholar 

  35. Sato, Y., Miya, M., Fukunaga, T., Sado, T. & Iwasaki, W. MitoFish and mifish pipeline: a mitochondrial genome database of fish with an analysis pipeline for environmental DNA metabarcoding. Mol. Biol. Evol. 35, 1553–1555. https://doi.org/10.1093/molbev/msy074 (2018).

    Google Scholar 

  36. Choi, J. W. & An, K. G. Characteristics of fish compositions and longitudinal distribution in Yeongsan river water-shed. Korean J. Ecol. Environ. 41, 301–310 (2008).

    Google Scholar 

  37. Choi, K. S., Han, M. S., Yoon, J. D. & Ko, M. H. Characteristics of fish community and the effects of water quality on river health in Sincheon, Imjin river, Korea. Korean J. Environ. Ecol. 35, 265–276. https://doi.org/10.13047/KJEE.2021.35.3.265 (2021).

    Google Scholar 

  38. Amin, M. H. F. Comparative analysis of benthic invertebrates and fish communities in three Korean streams using environmental DNA metabarcoding. PhD thesis, Pukyong National University (2022).

  39. Lee, H. J. et al. Seasonal variation in longitudinal connectivity for fish community in the Hotancheon from the geum River, as assessed by environmental DNA metabarcoding. J. Ecol. Environ. 48, 5. https://doi.org/10.5141/jee.23.067 (2024).

    Google Scholar 

  40. Park, S. K. & Joo, H. S. Fish fauna in the Seomjin River, Korea. Korean J. Environ. Biol. 33, 314–329. https://doi.org/10.11626/KJEB.2015.33.3.314 (2015).

    Google Scholar 

  41. Tamura, K., Stecher, G. & Kumar, S. MEGA11: molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 38, 3022–3027. https://doi.org/10.1093/molbev/msab120 (2021).

    Google Scholar 

  42. Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F. & Higgins, D. G. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 25, 4876–4882. https://doi.org/10.1093/nar/25.24.4876 (1997).

    Google Scholar 

  43. Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 34, 3299–3302. https://doi.org/10.1093/molbev/msx248 (2017).

    Google Scholar 

  44. Clement, M., Posada, D. & Crandall, K. A. TCS: a computer program to estimate gene genealogies. Mol. Ecol. 9, 1657–1659. https://doi.org/10.1046/j.1365-294x.2000.01020.x (2000).

    Google Scholar 

  45. Leigh, J. W., Bryant, D. & Nakagawa, S. POPART: full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116. https://doi.org/10.1111/2041-210X.12410 (2015).

    Google Scholar 

  46. Miller, M. A. et al. A RESTful API for access to phylogenetic tools via the CIPRES science gateway. Evol. Bioinform. 11, EBO-S21501; (2015). https://doi.org/10.4137/EBO.S21501

  47. Lanfear, R., Frandsen, P. B., Wright, A. M., Senfeld, T. & Calcott, B. PartitionFinder 2: new methods for selecting partitioned models of evolution for molecular and morphological phylogenetic analyses. Mol. Biol. Evol. 34, 772–773. https://doi.org/10.1093/molbev/msw260 (2017).

    Google Scholar 

  48. Guindon, S. & Gascuel, O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52, 696–704. https://doi.org/10.1080/10635150390235520 (2003).

    Google Scholar 

  49. Ronquist, F. & Huelsenbeck, J. P. MrBayes 3: bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572–1574. https://doi.org/10.1093/bioinformatics/btg180 (2003).

    Google Scholar 

  50. Letunic, I. & Bork, P. Interactive tree of life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics 23, 127–128. https://doi.org/10.1093/bioinformatics/btl529 (2007).

    Google Scholar 

  51. Pons, J. et al. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Syst. Biol. 55, 595–609. https://doi.org/10.1080/10635150600852011 (2006).

    Google Scholar 

  52. Puillandre, N., Lambert, A., Brouillet, S. & Achaz, G. ABGD, automatic barcode gap discovery for primary species delimitation. Mol. Ecol. 21, 1864–1877. https://doi.org/10.1111/j.1365-294X.2011.05239.x (2012).

    Google Scholar 

  53. Puillandre, N., Brouillet, S. & Achaz, G. ASAP: assemble species by automatic partitioning. Mol. Ecol. Resour. 21, 609–620. https://doi.org/10.1111/1755-0998.13281 (2021).

    Google Scholar 

  54. Zhang, J., Kapli, P., Pavlidis, P. & Stamatakis, A. A general species delimitation method with applications to phylogenetic placements. Bioinformatics 29, 2869–2876. https://doi.org/10.1093/bioinformatics/btt499 (2013).

    Google Scholar 

  55. Vences, M. et al. iTaxoTools 0.1: kickstarting a specimen-based software toolkit for taxonomists. Megataxa 6, 77–92. https://doi.org/10.11646/megataxa.6.2.1 (2021).

    Google Scholar 

  56. Drummond, A. J. & Rambaut, A. BEAST: bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7, 214. https://doi.org/10.1186/1471-2148-7-214 (2007).

    Google Scholar 

  57. Ezard, T., Fujisawa, T. & Barraclough, T. G. SPLITS: species’ limits by threshold statistics. R package version 1.0–18/r45. (2009). http://R-Forge.R-project.org/projects/splits

  58. Mello, B. Estimating timetrees with MEGA and the timetree resource. Mol. Biol. Evol. 35, 2334–2342. https://doi.org/10.1093/molbev/msy133 (2018).

    Google Scholar 

  59. Tamura, K., Tao, Q. & Kumar, S. Theoretical foundation of the RelTime method for estimating divergence times from variable evolutionary rates. Mol. Biol. Evol. 35, 1770–1782. https://doi.org/10.1093/molbev/msy044 (2018).

    Google Scholar 

  60. Mello, B., Tao, Q., Tamura, K. & Kumar, S. Fast and accurate estimates of divergence times from big data. Mol. Biol. Evol. 34, 45–50. https://doi.org/10.1093/molbev/msw247 (2017).

    Google Scholar 

  61. Tamura, K. et al. Estimating divergence times in large molecular phylogenies. Proc. Natl. Acad. Sci. U S A. 109, 19333–19338. https://doi.org/10.1073/pnas.1213199109 (2012).

    Google Scholar 

  62. Crossley, B. M. et al. Guidelines for Sanger sequencing and molecular assay monitoring. J. Vet. Diagn. Invest. 32, 767–775. https://doi.org/10.1177/1040638720905833 (2020).

    Google Scholar 

  63. Chen, W., Zhong, Z., Dai, W., Fan, Q. & He, S. Phylogeographic structure, cryptic speciation and demographic history of the sharpbelly (Hemiculter leucisculus), a freshwater habitat generalist from Southern China. BMC Evol. Biol. 17, 1–13. https://doi.org/10.1186/s12862-017-1058-0 (2017).

    Google Scholar 

  64. Won, H., Jeon, H. B. & Suk, H. Y. Evidence of an ancient connectivity and biogeodispersal of a Bitterling species, Rhodeus notatus, across the Korean Peninsula. Sci. Rep. 10, 1011. https://doi.org/10.1038/s41598-020-57625-3 (2020).

    Google Scholar 

  65. Liu, J. Q., Wang, Y. J., Wang, A. L., Hideaki, O. & Abbott, R. J. Radiation and diversification within the Ligularia–Cremanthodium–Parasenecio complex (Asteraceae) triggered by uplift of the Qinghai-Tibetan plateau. Mol. Phylogenet Evol. 38, 31–49. https://doi.org/10.1016/j.ympev.2005.09.010 (2006).

    Google Scholar 

  66. Rundle, H. D. (ed, P.) Ecological speciation. Ecol. Lett. 8 336–352 https://doi.org/10.1111/j.1461-0248.2004.00715.x (2005).

    Google Scholar 

  67. Chough, S., Kwon, S. T., Ree, J. H. & Choi, D. Tectonic and sedimentary evolution of the Korean peninsula: a review and new view. Earth-Sci. Rev. 52, 175–235. https://doi.org/10.1016/S0012-8252(00)00029-5 (2000).

    Google Scholar 

  68. Kwon, S., Kim, J., Lee, E. H. & Jung, C. Y. Geography of Korea: the Understanding Korea Series (UKS) 7 (The Academy of Korean Studies, 2016).

  69. Yoon, J. D., Kim, J. H., Park, S. H. & Jang, M. H. The distribution and diversity of freshwater fishes in Korean Peninsula. Korean J. Ecol. Environ. 51, 71–85. https://doi.org/10.11614/KSL.2018.51.1.071 (2018).

    Google Scholar 

  70. Kim, I. S., Park, J. Y. & Nalbant, T. T. A new species of Koreocobitis from Korea with a redescription of K. rotundicaudata. Korean J. Ichthyol. 12, 89–95 (2000).

    Google Scholar 

  71. Jang, J. E. et al. Genetic diversity and genetic structure of the endangered Manchurian trout, Brachymystax Lenok tsinlingensis, at its Southern range margin: conservation implications for future restoration. Conserv. Genet. 18, 1023–1036. https://doi.org/10.1007/s10592-017-0953-7 (2017).

    Google Scholar 

  72. Jeon, H. B., Song, H. Y., Suk, H. Y. & Bang, I. C. Phylogeography of the Korean endemic Coreoleuciscus (Cypriniformes: Gobionidae): the genetic evidence of colonization through Eurasian continent to the Korean Peninsula during late Plio-Pleistocene. Genes Genom. 44, 709–719. https://doi.org/10.1007/s13258-022-01243-y (2022).

    Google Scholar 

  73. Jeon, H. B. & Suk, H. Y. Genetic structure of Rhodeus sinensis reflects historical imprints of East Asian paleo-drainages. Anim. Cells Syst. 27, 353–365. https://doi.org/10.1080/19768354.2023.2285829 (2023).

    Google Scholar 

  74. Zhang, J. et al. History of yellow river and Yangtze river delivering sediment to the yellow sea since 3.5 Ma: tectonic or climate forcing? Quat Sci. Rev. 216, 74–88. https://doi.org/10.1016/j.quascirev.2019.06.002 (2019).

    Google Scholar 

  75. Taniguchi, S., Bertl, J., Futschik, A., Kishino, H. & Okazaki, T. Waves out of the Korean Peninsula and inter-and intra-species replacements in freshwater fishes in Japan. Genes 12, 303. https://doi.org/10.3390/genes12020303 (2021).

    Google Scholar 

  76. Taberlet, P., Coissac, E., Pompanon, F., Brochmann, C. & Willerslev, E. Towards next-generation biodiversity assessment using DNA metabarcoding. Mol. Ecol. 21, 2045–2050. https://doi.org/10.1111/j.1365-294X.2012.05470.x (2012).

    Google Scholar 

  77. Jense, C. et al. Cryptic diversity within two widespread diadromous freshwater fishes (Teleostei: Galaxiidae). Ecol. Evol. 14, e11201. https://doi.org/10.1002/ece3.11201 (2024).

    Google Scholar 

  78. Chen, T., Jiao, L. & Ni, L. The phylogeographical pattern of the Amur minnow Rhynchocypris lagowskii (Cypriniformes: Cyprinidae) in the Qinling mountains. Ecol. Evol. 12, e8924. https://doi.org/10.1002/ece3.8924 (2022).

    Google Scholar 

  79. Oh, C. W., Sajeev, K., Kim, S. W. & Santosh, M. Tectonic evolution of Korean Peninsula and adjacent crustal fragments in asia: introduction. Gondwana Res. 9, 19–20. https://doi.org/10.1016/j.gr.2005.07.001 (2006).

    Google Scholar 

  80. Kim, D., Hirt, M. V., Won, Y. J. & Simons, A. M. Small fishes crossed a large mountain range: quaternary stream capture events and freshwater fishes on both sides of the Taebaek mountains. Integr. Zool. 12, 292–302. https://doi.org/10.1111/1749-4877.12228 (2017).

    Google Scholar 

  81. Yun, B. H., Kim, Y. H., Han, H. S. & Bang, I. C. Population genetics analysis based on mitochondrial cytochrome c oxidase subunit I (CO1) gene sequences of Cottus Koreanus in South Korea. Genes Genom. 47, 207–221. https://doi.org/10.1007/s13258-024-01600-z (2025).

    Google Scholar 

  82. Kim, D. E., Seong, Y. B., Weber, J. & Yu, B. Y. Unsteady migration of Taebaek Mountain drainage divide, Cenozoic extensional basin margin, Korean Peninsula. Geomorphology 352, 107012; (2020). https://doi.org/10.1016/j.geomorph.2019.107012

  83. Fricke, R., Eschmeyer, W. N. & Van der Laan, R. (eds) Eschmeyer’s Catalog of Fishes: Genera, Species, References. (2025). http://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp accessed 11 March 2025).

  84. Hata, H., Fujita, T., Watanabe, S. & Hosoya, K. Current status of two closely related Phoxinus species, in the Ishi river (Yamato river basin), Osaka Prefecture, Japan. Jpn J. Ichthyol. 66, 15–22. https://doi.org/10.11369/jji.18-30 (2019).

    Google Scholar 

  85. Fujita, T. & Hosoya, K. Biochemical and morphological comparison between two Japanese daces, Phoxinus lagowskii steindachneri and P. oxycephalus Jouyi in the sympatric sites. Jpn J. Ichthyol. 50, 55–62. https://doi.org/10.11369/jji1950.50.55 (2003).

    Google Scholar 

  86. Imoto, J. M. et al. Phylogeny and biogeography of highly diverged freshwater fish species (Leuciscinae, Cyprinidae, Teleostei) inferred from mitochondrial genome analysis. Gene 514, 112–124. https://doi.org/10.1016/j.gene.2012.10.019 (2013).

    Google Scholar 

  87. Jeon, H. B. Evolutionary history of Acheilognathid fish inferred based on genetic and genomic analyses. PhD thesis, Yeungnam University (2018).

  88. Jeon, H. B., Kim, D. Y., Lee, Y. J., Bae, H. G. & Suk, H. Y. The genetic structure of Squalidus multimaculatus revealing the historical pattern of serial colonization on the tip of East Asian continent. Sci. Rep. 8, 10629. https://doi.org/10.1038/s41598-018-28340-x (2018).

    Google Scholar 

Download references

Acknowledgements

The authors wish to express their profound gratitude to the laboratory colleagues of the Molecular Physiology Laboratory, Department of Marine Biology, Pukyong National University for their support during this research.

Funding

This work was supported by Dongwon Research Foundation in 2024 (202404170001) and the corresponding author (Hyun-Woo Kim) was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2021-NR060118).

Author information

Authors and Affiliations

Authors

Contributions

S.K. and H.-W.K. conceived and supervised the study. G.B., S.R.L., and H.H. performed the experiments. G.B., H.-E.K., and A.R.K. performed the data analyses. M.Y., H.J.K., I.A. and M.H.F.A. contributed to the data analyses. G.B., S.K., and H.-W.K. wrote the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to
Shantanu Kundu or Hyun-Woo Kim.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethical accordance for procedures

The study is entirely based on environmental water samples; therefore, no animal samples were collected from the wild, and no special permissions were required for this research.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Bang, G., Lee, S.R., Kang, HE. et al. Environmental DNA reveals the distinct genetic diversity and evolutionary pathways of the Chinese Minnow Rhynchocypris oxycephalus in Korean freshwater systems.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-32073-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-025-32073-z


Source: Ecology - nature.com

… of the Year

Circovirus infection in Croatian population of Eurasian griffon vultures (Gyps fulvus)

Back to Top